Vincent Stimper
Impact in
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- Image Enhancement Techniques
- Advanced Image Processing Techniques
- Advanced Neural Network Applications
- Image and Signal Denoising Methods
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- Advanced Image Fusion Techniques
Papers in
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- Generative Adversarial Networks and Image Synthesis 2
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- Stochastic Gradient Optimization Techniques 1
- Co-authors
- Bernhard Schölkopf (3 shared papers)Ralph Ernstorfer (2 shared papers)R. Patrick Xian (2 shared papers)Stefan Bauer (2 shared papers)David Liu (1 shared paper)Andrew T. Campbell (1 shared paper)Vincent Berenz (1 shared paper)José Miguel Hernández-Lobato (2 shared papers)
- Journals
- Nature Computational Science (1 paper)IEEE Access (1 paper)Machine Learning Science and Technology (1 paper)Apollo (University of Cambridge) (1 paper)The Journal of Open Source Software (1 paper)
- Partner nations
- GermanyUnited KingdomUnited States
In The Last Decade
Vincent Stimper
4 papers receiving 80 citations
Peers
Comparison fields: 5 of 49
- Computer Vision and Pattern Recognition 31
- Media Technology 8
- Biophysics 5
- Structural Biology 1
- Radiology, Nuclear Medicine and Imaging 16
Countries citing papers authored by Vincent Stimper
This map shows the geographic impact of Vincent Stimper's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Vincent Stimper with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vincent Stimper more than expected).
Fields of papers citing papers by Vincent Stimper
This network shows the impact of papers produced by Vincent Stimper. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Vincent Stimper. The network helps show where Vincent Stimper may publish in the future.
Co-authors
The 19 scholars most cited alongside Vincent Stimper, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 57 | |
| 2 | 2023 | 16 | |
| 3 | 2022 | 10 | |
| 4 | 2025 | 2 | |
| 5 | 2021 | 1 |
About Vincent Stimper
Vincent Stimper is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Statistical and Nonlinear Physics, Biophysics and Nuclear and High Energy Physics, having authored 5 papers that have together received 86 indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (2 papers), Particle physics theoretical and experimental studies (1 paper), Quantum Chromodynamics and Particle Interactions (1 paper), Cell Image Analysis Techniques (1 paper), Electronic and Structural Properties of Oxides (1 paper), High-Energy Particle Collisions Research (1 paper), Stochastic Gradient Optimization Techniques (1 paper) and Markov Chains and Monte Carlo Methods (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (31 citations), Media Technology (8 citations), Biophysics (5 citations), Structural Biology (1 citation) and Radiology, Nuclear Medicine and Imaging (16 citations). Vincent Stimper has collaborated with scholars based in Germany, United Kingdom and United States. Frequent co-authors include Bernhard Schölkopf, Ralph Ernstorfer, R. Patrick Xian, Stefan Bauer, David Liu, Andrew T. Campbell, Vincent Berenz, José Miguel Hernández-Lobato, Laurenz Rettig and Maciej Dendzik. Their work appears in journals such as Nature Computational Science, IEEE Access, Machine Learning Science and Technology, Apollo (University of Cambridge) and The Journal of Open Source Software.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.